OpenRaiser/Intern-Atlas huggingface dataset:
Discriminative Features via Generalized Eigenvectors
Venue: arXiv cs.LG 2013
Year: 2013

Representing examples in a way that is compatible with the underlying classifier can greatly enhance the performance of a learning system. In this paper we investigate scalable techniques for inducing discriminative features by taking advantage of simple second order structure in the data. We focus on multiclass classification and show that features extracted from the generalized eigenvectors of the class conditional second moments lead to classifiers with excellent empirical performance. Moreover, these features have attractive theoretical properties, such as inducing representations that are invariant to linear transformations of the input. We evaluate classifiers built from these features on three different tasks, obtaining state of the art results.
Codebook-Based Opportunistic Interference Alignment
Venue: arXiv cs.IT 2013
Year: 2013

Opportunistic interference alignment (OIA) asymptotically achieves the optimal degrees-of-freedom (DoF) in interfering multiple-access channels (IMACs) in a distributed fashion, as a certain user scaling condition is satisfied. For the multiple-input multiple-output IMAC, it was shown that the singular value decomposition (SVD)-based beamforming at the users fundamentally reduces the user scaling condition required to achieve any target DoF compared to that for the single-inputmultiple-output IMAC. In this paper, we tackle two practical challenges of the existing SVD-based OIA: 1) the need of full feedforward of the selected users' beamforming weight vectors and 2) a low rate achieved based on the exiting zero-forcing (ZF) receiver. We first propose a codebook-based OIA, in which the weight vectors are chosen from a pre-defined codebook with a finite size so that information of the weight vectors can be sent to the belonging BS with limited feedforward. We derive the codebook size required to achieve the same user scaling condition as the SVD-based OIA case for both Grassmannian and random codebooks. Surprisingly, it is shown that the derived codebook size is the same for the two considered codebook approaches. Second, we take into account an enhanced receiver at the base stations (BSs) in pursuit of improving the achievable rate based on the ZF receiver. Assuming no collaboration between the BSs, the interfering links between a BS and the selected users in neighboring cells are difficult to be acquired at the belonging BS. We propose the use of a simple minimum Euclidean distance receiver operating with no information of the interfering links. With the help of the OIA, we show that this new receiver asymptotically achieves the channel capacity as the number of users increases.
Step-Indexed Relational Reasoning for Countable Nondeterminism
Venue: arXiv cs.LO 2013
Year: 2013

Programming languages with countable nondeterministic choice are computationally interesting since countable nondeterminism arises when modeling fairness for concurrent systems. Because countable choice introduces non-continuous behaviour, it is well-known that developing semantic models for programming languages with countable nondeterminism is challenging. We present a step-indexed logical relations model of a higher-order functional programming language with countable nondeterminism and demonstrate how it can be used to reason about contextually defined may- and must-equivalence. In earlier step-indexed models, the indices have been drawn from ω. Here the step-indexed relations for must-equivalence are indexed over an ordinal greater than ω.
Coordinated Beamforming for Energy Efficient Transmission in Multicell Multiuser Systems
Venue: arXiv cs.IT 2013
Year: 2013

In this paper we study energy efficient joint power allocation and beamforming for coordinated multicell multiuser downlink systems. The considered optimization problem is in a non-convex fractional form and hard to tackle. We propose to first transform the original problem into an equivalent optimization problem in a parametric subtractive form, by which we reach its solution through a two-layer optimization scheme. The outer layer only involves one-dimension search for the energy efficiency parameter which can be addressed using the bi-section search, the key issue lies in the inner layer where a non-fractional sub-problem needs to tackle. By exploiting the relationship between the user rate and the mean square error, we then develop an iterative algorithm to solve it. The convergence of this algorithm is proved and the solution is further derived in closed-form. Our analysis also shows that the proposed algorithm can be implemented in parallel with reasonable complexity. Numerical results illustrate that our algorithm has a fast convergence and achieves near-optimal energy efficiency. It is also observed that at the low transmit power region, our solution almost achieves the optimal sum rate and the optimal energy efficiency simultaneously; while at the middle-high transmit power region, a certain sum rate loss is suffered in order to guarantee the energy efficiency.
Double four-bar crank-slider mechanism dynamic balancing by meta-heuristic algorithms
Venue: arXiv cs.AI 2013
Year: 2013

In this paper, a new method for dynamic balancing of double four-bar crank slider mechanism by meta- heuristic-based optimization algorithms is proposed. For this purpose, a proper objective function which is necessary for balancing of this mechanism and corresponding constraints has been obtained by dynamic modeling of the mechanism. Then PSO, ABC, BGA and HGAPSO algorithms have been applied for minimizing the defined cost function in optimization step. The optimization results have been studied completely by extracting the cost function, fitness, convergence speed and runtime values of applied algorithms. It has been shown that PSO and ABC are more efficient than BGA and HGAPSO in terms of convergence speed and result quality. Also, a laboratory scale experimental doublefour-bar crank-slider mechanism was provided for validating the proposed balancing method practically.
On client interactive behaviour to design peer selection policies for BitTorrent-like protocols
Venue: arXiv cs.NI 2013
Year: 2013

Peer-to-peer swarming protocols have been proven to be very efficient for content replication over Internet. This fact has certainly motivated proposals to adapt these protocols to meet the requirements of on-demand streaming system. The vast majority of these proposals focus on modifying the piece and peer selection policies, respectively, of the original protocols. Nonetheless, it is true that more attention has often been given to the piece selection policy rather than to the peer selection policy. Within this context, this article proposes a simple algorithm to be used as basis for peer selection policies of BitTorrent-like protocols, considering interactive scenarios. To this end, we analyze the client interactive behaviour when accessing real multimedia systems. This analysis consists of looking into workloads of real content providers and assessing three important metrics, namely temporal dispersion, spatial dispersion and object position popularity. These metrics are then used as the main guidelines for writing the algorithm. To the best of our knowledge, this is the first time that the client interactive behaviour is specially considered to derive an algorithm for peer selection policies. Finally, the conclusion of this article is drawn with key challenges and possible future work in this research field.
Group lifting structures for multirate filter banks I: Uniqueness of lifting factorizations
Venue: arXiv cs.IT 2013
Year: 2013

Group lifting structures are introduced to provide an algebraic framework for studying lifting factorizations of two-channel perfect reconstruction finite-impulse-response (FIR) filter banks. The lifting factorizations generated by a group lifting structure are characterized by Abelian groups of lower and upper triangular lifting matrices, an Abelian group of unimodular gain scaling matrices, and a set of base filter banks. Examples of group lifting structures are given for linear phase lifting factorizations of the two nontrivial classes of two-channel linear phase FIR filter banks, the whole- and half-sample symmetric classes, including both the reversible and irreversible cases. This covers the lifting specifications for whole-sample symmetric filter banks in Parts 1 and 2 of the ISO/IEC JPEG 2000 still image coding standard. The theory is used to address the uniqueness of lifting factorizations. With no constraints on the lifting process, it is shown that lifting factorizations are highly nonunique. When certain hypotheses developed in the paper are satisfied, however, lifting factorizations generated by a group lifting structure are shown to be unique. A companion paper applies the uniqueness results proven in this paper to the linear phase group lifting structures for whole- and half-sample symmetric filter banks.
Interactive Function Computation with Reconstruction Constraints
Venue: arXiv cs.IT 2013
Year: 2013

This paper investigates two-terminal interactive function computation with reconstruction constraints. Each terminal wants to compute a (possibly different) function of two correlated sources, but can only access one of the sources directly. In addition to distortion constraints at the terminals, each terminal is required to estimate the computed function value at the other terminal in a lossy fashion, leading to the constrained reconstruction constraint. A special case of constrained reconstruction is the common reconstruction constraint, in which both terminals agree on the functions computed with probability one. The terminals exchange information in multiple rate constrained communication rounds. A characterization of the multi-round rate-distortion region for the above problem with constrained reconstruction constraints is provided. To gain more insights and to highlight the value of interaction and order of communication, the rate-distortion region for computing various functions of jointly Gaussian sources according to common reconstruction constraints is studied.
SAT-based Preprocessing for MaxSAT (extended version)
Venue: arXiv cs.AI 2013
Year: 2013

State-of-the-art algorithms for industrial instances of MaxSAT problem rely on iterative calls to a SAT solver. Preprocessing is crucial for the acceleration of SAT solving, and the key preprocessing techniques rely on the application of resolution and subsumption elimination. Additionally, satisfiability-preserving clause elimination procedures are often used. Since MaxSAT computation typically involves a large number of SAT calls, we are interested in whether an input instance to a MaxSAT problem can be preprocessed up-front, i.e. prior to running the MaxSAT solver, rather than (or, in addition to) during each iterative SAT solver call. The key requirement in this setting is that the preprocessing has to be sound, i.e. so that the solution can be reconstructed correctly and efficiently after the execution of a MaxSAT algorithm on the preprocessed instance. While, as we demonstrate in this paper, certain clause elimination procedures are sound for MaxSAT, it is well-known that this is not the case for resolution and subsumption elimination. In this paper we show how to adapt these preprocessing techniques to MaxSAT. To achieve this we recast the MaxSAT problem in a recently introduced labelled-CNF framework, and show that within the framework the preprocessing techniques can be applied soundly. Furthermore, we show that MaxSAT algorithms restated in the framework have a natural implementation on top of an incremental SAT solver. We evaluate the prototype implementation of a MaxSAT algorithm WMSU1 in this setting, demonstrate the effectiveness of preprocessing, and show overall improvement with respect to non-incremental versions of the algorithm on some classes of problems.
Middle-Solving F4 to Compute Grobner bases for Cryptanalysis over GF(2)
Venue: arXiv cs.SC 2013
Year: 2013

Algebraic cryptanalysis usually requires to recover the secret key by solving polynomial equations. Faugere's F4 is a well-known Grobner bases algorithm to solve this problem. However, a serious drawback exists in the Grobner bases based algebraic attacks, namely, any information won't be got if we couldn't work out the Grobner bases of the polynomial equations system. In this paper, we in-depth research the F4 algorithm over GF(2). By using S-polynomials to replace critical pairs and computing the normal form of the productions with respect to the field equations in certain steps, many "redundant" reductors are avoided during the computation process of the F4 algorithm. By slightly modifying the logic of F4 algorithm, we solve the univariate polynomials appeared in the algorithm and then back-substitute the values of the solved variables at each iteration of the algorithm. We call our improvements Middle-Solving F4. The heuristic strategy of Middle-Solving overcomes the drawback of algebraic attacks and well suits algebraic attacks. It has never been applied to the Grobner bases algorithm before. Experiments to some Hidden Field Equation instances and some classical benchmarks (Cyclic 6, Gonnet83) show that Middle-Solving F4 is faster and uses less memory than Faugere's F4.
Discriminative Relational Topic Models
Venue: arXiv cs.LG 2013
Year: 2013

Many scientific and engineering fields involve analyzing network data. For document networks, relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in common real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving the prediction performance, and the time efficiency can be dramatically improved with a simple fast approximation method.
Combining Ontologies with Correspondences and Link Relations: The E-SHIQ Representation Framework
Venue: arXiv cs.AI 2013
Year: 2013

Combining knowledge and beliefs of autonomous peers in distributed settings, is a ma- jor challenge. In this paper we consider peers that combine ontologies and reason jointly with their coupled knowledge. Ontologies are within the SHIQ fragment of Description Logics. Although there are several representation frameworks for modular Description Log- ics, each one makes crucial assumptions concerning the subjectivity of peers' knowledge, the relation between the domains over which ontologies are interpreted, the expressivity of the constructors used for combining knowledge, and the way peers share their knowledge. However in settings where autonomous peers can evolve and extend their knowledge and beliefs independently from others, these assumptions may not hold. In this article, we moti- vate the need for a representation framework that allows peers to combine their knowledge in various ways, maintaining the subjectivity of their own knowledge and beliefs, and that reason collaboratively, constructing a tableau that is distributed among them, jointly. The paper presents the proposed E-SHIQ representation framework, the implementation of the E-SHIQ distributed tableau reasoner, and discusses the efficiency of this reasoner.
MizAR 40 for Mizar 40
Venue: arXiv cs.AI 2013
Year: 2013

As a present to Mizar on its 40th anniversary, we develop an AI/ATP system that in 30 seconds of real time on a 14-CPU machine automatically proves 40% of the theorems in the latest official version of the Mizar Mathematical Library (MML). This is a considerable improvement over previous performance of large- theory AI/ATP methods measured on the whole MML. To achieve that, a large suite of AI/ATP methods is employed and further developed. We implement the most useful methods efficiently, to scale them to the 150000 formulas in MML. This reduces the training times over the corpus to 1-3 seconds, allowing a simple practical deployment of the methods in the online automated reasoning service for the Mizar users (MizAR).
Precoding Based Network Alignment using Transform Approach for Acyclic Networks with Delay
Venue: arXiv cs.IT 2013
Year: 2013

The algebraic formulation for linear network coding in acyclic networks with the links having integer delay is well known. Based on this formulation, for a given set of connections over an arbitrary acyclic network with integer delay assumed for the links, the output symbols at the sink nodes, at any given time instant, is a $\mathbb{F}_{p^m}$-linear combination of the input symbols across different generations where, $\mathbb{F}_{p^m}$ denotes the field over which the network operates ($p$ is prime and $m$ is a positive integer). We use finite-field discrete fourier transform (DFT) to convert the output symbols at the sink nodes, at any given time instant, into a $\mathbb{F}_{p^m}$-linear combination of the input symbols generated during the same generation without making use of memory at the intermediate nodes. We call this as transforming the acyclic network with delay into {\em $n$-instantaneous networks} ($n$ is sufficiently large). We show that under certain conditions, there exists a network code satisfying sink demands in the usual (non-transform) approach if and only if there exists a network code satisfying sink demands in the transform approach. When the zero-interference conditions are not satisfied, we propose three Precoding Based Network Alignment (PBNA) schemes for three-source three-destination multiple unicast network with delays (3-S 3-D MUN-D) termed as PBNA using transform approach and time-invariant local encoding coefficients (LECs), PBNA using time-varying LECs, and PBNA using transform approach and block time-varying LECs. Their feasibility conditions are then analyzed.
Interactive Computation of Type-Threshold Functions in Collocated Broadcast-Superposition Networks
Venue: arXiv cs.IT 2013
Year: 2013

In wireless sensor networks, various applications involve learning one or multiple functions of the measurements observed by sensors, rather than the measurements themselves. This paper focuses on type-threshold functions, e.g., the maximum and indicator functions. Previous work studied this problem under the collocated collision network model and showed that under many probabilistic models for the measurements, the achievable computation rates converge to zero as the number of sensors increases. This paper considers two network models reflecting both the broadcast and superposition properties of wireless channels: the collocated linear finite field network and the collocated Gaussian network. A general multi-round coding scheme exploiting not only the broadcast property but particularly also the superposition property of the networks is developed. Through careful scheduling of concurrent transmissions to reduce redundancy, it is shown that given any independent measurement distribution, all type-threshold functions can be computed reliably with a non-vanishing rate in the collocated Gaussian network, even if the number of sensors tends to infinity.
Informational Divergence and Entropy Rate on Rooted Trees with Probabilities
Venue: arXiv cs.IT 2013
Year: 2013

Rooted trees with probabilities are used to analyze properties of a variable length code. A bound is derived on the difference between the entropy rates of the code and a memoryless source. The bound is in terms of normalized informational divergence. The bound is used to derive converses for exact random number generation, resolution coding, and distribution matching.
Joint DOA and Array Manifold Estimation for a MIMO Array Using Two Calibrated Antennas
Venue: arXiv cs.IT 2013
Year: 2013

A simple scheme for joint direction of arrival (DOA) and array manifold estimation for a MIMO array system is proposed, where only two transmit antennas are calibrated initially. It first obtains a set of initial DOA results by employing a rotational invariance property between two sets of received data, and then more accurate DOA and array manifold estimation is obtained through a local searching algorithm with several iterations. No strict half wavelength spacing is required for the uncalibrated antennas to avoid the spatial aliasing problem.
Inventions on reducing keyboard size: A TRIZ based analysis
Venue: arXiv cs.HC 2013
Year: 2013

A conventional computer keyboard consists of as many as 101 keys. The keyboard has several sections, such as text entry section, navigation section, and numeric keypad etc. and each having several keys on the keyboard. The size of the keyboard is a major inconvenience for portable computers, as they cannot be carried easily. Thus there are certain circumstances which compels to reduce the size of a keyboard. Reducing the size of a keyboard leads to several problems. A reduced size keyboard may not contain all the keys available on a full size keyboard; a reduced size keyboard may not be convenient to operate, a reduced size keyboard may have a different key layout which is difficult to learn etc. This article illustrates 10 inventions on reducing the size of the keyboard. Various inventions have attempted to solve the contradictions so that the user achieves the benefits of both "reduced size" and "typing comfort".
Implementation of the Cluster Based Tunable Sleep Transistor Cell Power Gating Technique for a 4x4 Multiplier Circuit
Venue: arXiv cs.OH 2013
Year: 2013

A modular, programmable, and high performance Power Gating strategy, called cluster based tunable sleep transistor cell Power Gating, has been introduced in the present paper with a few modifications. Furthermore, a detailed comparison of its performance with some of the other conventional Power Gating schemes; such as Cluster Based Sleep Transistor Design (CBSTD), Distributed Sleep Transistor Network (DSTN) etc.; has also been presented here. Considering the constraints of power consumption, performance, and the area overhead, while doing the actual implementation of any Power Gating scheme, it becomes important to deal with the various design issues like the proper sizing of the sleep transistors (STs), controlling the voltage drop (IR drop) across the STs, and obviously maintaining a desired performance with lower amount of delay degradation. With this notion, we tried to find out an efficient Power Gating strategy which can reduce the overall power consumption of any CMOS circuit by virtue of reducing the standby mode leakage current. Taking the different performance parameters into account, for an example circuit, which is actually the conventional 4x4 multiplier design, we found that the modified tunable sleep transistor cell Power Gating gives very much promising results. The reported architecture of the 4x4 multiplier with the tunable sleep transistor cell Power Gating, is designed using 45 nm technology and it consumes 1.3638x10-5 Watt of Average Power while being operated with the nominal case of the bit configuration word, that is, 1000. ...........